range-Doppler Method Research Articles

A Novel Comb-line Leaky-wave Antenna for 77 GHz FMCW Automotive Radar System and Comparison with Buttler Beamformers

For a typical frequency modulated continuous wave automotive radar system, a design using a novel leaky-wave antenna is proposed that has a simple, cheap and easy manufacturing structure whose performance is compared with two different antenna arrays. The software used were MATLAB and CST Microwave Studio. The first antenna system was an inset-fed patch array, and the second antenna system was a circular patch array with a Buttler beamforming network as a beam scanning mechanism. The simulation results of the three proposed designs are obtained using the range-Doppler method for multi-target scenarios. The proposed leaky-wave antenna excels the antenna arrays, which offer cheaper and simpler solutions for the automotive industry.

A Range-Doppler Method for Focusing Radar Sounder Data Generated by Coherent Electromagnetic Simulators

Radar sounders (RS) are gaining importance in planetary missions thanks to their unique capability of providing direct measurements of subsurface structures. To support their design and data interpretation, several electromagnetic (e.m.) simulation techniques have been developed with enhanced capabilities of emulating the RS acquisition process. However, the raw simulated radargrams obtained from e.m. simulators are difficult to interpret and analyze without a focusing operation, which results in an underestimation of the RS detection performance. While frequency methods for range and azimuth compression of real RS data are well-established, their use on simulated data is not addressed in the literature and requires major modifications. This paper presents a novel method that implements azimuth compression using unfocused and focused processing on simulated raw data. The proposed method is based on an adaptation of the Range-Doppler algorithm to the case of raw data generated by a coherent RS simulator. The method is demonstrated in three case-studies to show the similarity between simulated and real data processing: 1) simple geometries; 2) a simulated SHARAD radargram compared with the real data product; and 3) a real application scenario for supporting the design of a new RS instrument. The results indicate higher fidelity of the focused simulated data with the real data product and the target structure, confirming the usefulness of the proposed approach in obtaining a realistic processing of simulated radargrams.

Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction

To achieve the high-resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems, and the imaging results can be improved. To solve these problems and improve the image quality, the problem of ISAR imaging is termed as a block-sparse signal recovery problem by utilizing the block-sparse structure of the ISAR images. A localized low-rank promoting (LLP) method is introduced and extended to the complex case for the recovery of range compressed block-sparse signals. The sparse recovery problem is solved by minimizing another function, which is the surrogate function that can be solved more effectively. Based on the LLP method, the coefficients of the range compressed echo signal are reconstructed and some 2 × 2 matrices can be obtained. And then the log-determinant function is introduced to find the low rankness solutions for these matrices. Then the LLP method is also used in the cross-range domain to reconstruct the ISAR image. Experimental results show that the proposed method can recover better focused and higher quality ISAR images compared with the traditional methods.

Novel sparse apertures ISAR imaging algorithm via the TLS‐ESPRIT technique

The prevalent imaging method in inverse synthetic aperture radar (ISAR) system is range-Doppler (RD) method, which is implemented by the fast Fourier transformation (FFT). FFT is computationally efficient, but it comes with a price – the problems of wide main-lobes and high side-lobes, especially under the sparse apertures condition. In addition, the resolution of RD method is determined by the radar parameters, which poses limitation to super-resolution imaging, multi-tasking and cognitive reconfigurable applications. In this study, the authors propose a novel super-resolution ISAR imaging method based on the total least squares-estimation of signal parameters via rotational invariance technique (TLS-ESPRIT). The locations and intensities of the scatterers are obtained by employing the ESPRIT algorithm and the least squares technique. Then the ISAR image is formulated, having circumvented all of the above-mentioned limitations. Experiments based on simulated and real measured data validate the effectiveness of the proposed method.

Frequency domain beamforming of ultrasound signals from inhomogeneous media using range Doppler method

Frequency domain beamforming methods, such as Stolt migration, yield efficient and fast processing of ultrasound data. Stolt migration, by migrating the individual element data in a 2-D frequency domain, improves processing speed by up to two orders of magnitude compared to conventional delay-and-sum (DAS) beamforming. However, as commonly implemented, it relies on the assumption that the speed-of-sound is constant, and is unable to be applied with advanced beamforming techniques such as phase aberration correction. Here, we demonstrate another approach to frequency domain beamforming, using the range-Doppler method developed for synthetic aperture radar imaging. The range-Doppler method is similar in speed to Stolt migration, but because it involves only a 1-D Fourier transform in array dimension, it can account for speed-of-sound inhomogeneities. We demonstrate our method with simulated channel signals of point targets and diffuse scatterers, and find similar image quality (e.g., mainlobe width, sidelobe levels, and contrast-to-noise ratio) to DAS beamforming in noise-free conditions. We further analyze signals acquired through a near-field phase-screen and from multi-layered media by modifying Doppler processing to correct for phase aberration and to account for the local sound-speed differences, respectively.

A Super-Resolution Sparse Aperture ISAR Sensors Imaging Algorithm via the MUSIC Technique

The conventional range-Doppler (RD) technique uses fast Fourier transformation (FFT) to generate focused images. However, the spectrum of FFT has high sidelobes and wide main lobes and the resolution of RD is limited by the radar parameters so that the RD method cannot generate super-resolution images especially with sparse aperture (SA) data. A super-resolution SA inverse synthetic aperture radar (SA-ISAR) imaging algorithm via the multiple signal classification (MUSIC) technique is proposed in this paper. The proposal uses the MUSIC algorithm to estimate the location and employs the least-squares technique to calculate the intensity of each scatterer. Then, the scatterers can be precisely depicted in the images without the interference of sidelobes and wide main lobes. The resolution of the proposal depends less on the radar parameters, and it can be further improved by using a smaller search step. Experiments obtained by processing of simulated and raw data demonstrate that the proposal can efficiently generate super-resolution images with full aperture (FA) or SA data.

Comparison between Range-Doppler and Rational-Function methods for SAR Terrain Geocoding

Geocoding of Synthetic Aperture Radar (SAR) imagery is an essential preprocessing step in multi-source data integration, management and analysis for many geomatics applications. The Range-Doppler (RD) approach is a rigorous physical sensor model, which achieves the highest geometric accuracy and has been widely used in terrain-geocoding of satellite SAR data. However the main drawback is that it is not computationally efficient. The Rational-Function (RF) model has been successfully used for processing of optical images (push broom sensors IKONOS and QuickBird), and is of considerable interest in processing of SAR datasets as an alternative to the RD method because of its high computational efficiency and fitting accuracy (e.g. RADARSAT-2). Two SAR terrain-geocoding methods, based on the RD and the RF models, have been implemented at Canada Center for Mapping and Earth Observation (CCMEO). In this paper we briefly describe the well-known RD mathematical model and the RF mathematical model in more detail. The relative geometric accuracy for the two methods is analysed and compared. Finally, some major advantages of the RF method over the RD method are presented.

Sub-Nyquist SAR via Fourier Domain Range-Doppler Processing

Conventional Synthetic Aperture Radar (SAR) systems are limited in their ability to satisfy the increasing requirement for improved spatial resolution and wider coverage. The demand for high resolution requires high sampling rates, while coverage is limited by the pulse repetition frequency. Consequently, sampling rate reduction is of high practical value in SAR imaging. In this paper, we introduce a new algorithm, equivalent to the well-known Range-Doppler method, to process SAR data using the Fourier series coefficients of the raw signals. We then demonstrate how to exploit the algorithm features to reduce sampling rate in both range and azimuth axes and process the signals at sub-Nyquist rates, by using compressed sensing (CS) tools. In particular, we demonstrate recovery of an image using only a portion of the received signal's bandwidth and also while dropping a large percentage of the transmitted pulses. The complementary pulses may be used to capture other scenes within the same coherent processing interval. In addition, we propose exploiting the ability to reconstruct the image from narrow bands in order to dynamically adapt the transmitted waveform energy to vacant spectral bands, paving the way to cognitive SAR. The proposed recovery algorithms form a new CS-SAR imaging method that can be applied to high-resolution SAR data acquired at sub-Nyquist rates in range and azimuth. The performance of our method is assessed using simulated and real data sets. Finally, our approach is implemented in hardware using a previously suggested Xampling radar prototype.

Fourier-sparsity integrated method for complex target ISAR imagery.

In existing sparsity-driven inverse synthetic aperture radar (ISAR) imaging framework a sparse recovery (SR) algorithm is usually applied to azimuth compression to achieve high resolution in the cross-range direction. For range compression, however, direct application of an SR algorithm is not very effective because the scattering centers resolved in the high resolution range profiles at different view angles always exhibit irregular range cell migration (RCM), especially for complex targets, which will blur the ISAR image. To alleviate the sparse recovery-induced RCM in range compression, a sparsity-driven framework for ISAR imaging named Fourier-sparsity integrated (FSI) method is proposed in this paper, which can simultaneously achieve better focusing performance in both the range and cross-range domains. Experiments using simulated data and real data demonstrate the superiority of our proposed framework over existing sparsity-driven methods and range-Doppler methods.

Fast geocoding of spaceborne synthetic-aperture radar images using graphics processing units

Geocoding is crucial for using remotely sensed data in almost all applications, especially when a combination of multiple data sources is required. However, geocoding a synthetic-aperture radar image with the standard range-Doppler method is a time-consuming process due to unavoidable iterations. Using a replacement sensor model, for example the rational polynomial camera (RPC) model, can significantly reduce the calculation time cost. Another way to improve the calculation efficiency is to use massively parallel processing techniques. Modern graphics processing units (GPU) can be used as parallel processing units for computationally intensive applications. Using NVIDIA's Compute Unified Device Architecture (CUDA) the implementation of the range-Doppler and RPC methods on GPUs is easy, because the existing C/C++ code can be reused. With further optimizations for GPU processing, tremendous improvements can be achieved. The CUDA implementations run about 10 to 30 times faster compared with similar implementations on the central processing unit (CPU), and almost 200 times faster if particularly optimized for GPU computing.

Reverse-Range-Doppler method for automated geocoding SAR images

Range-Doppler (RD) method and Reverse-Range-Doppler (RRD) method are combined together to achieve automatic geocoding of Synthetic Aperture Radar (SAR) image quickly and accurately in the paper. The RD method is firstly used to locate the four corners of the image, then the other pixels of the image can be located by Reverse-Range-Doppler (RRD) method. Resampling is performed at last. The approach has an advantage over previous techniques in that it does not require ground control points and is independent of spacecraft attitude knowledge or control. It can compensate the shift due to the assumed Doppler frequency in SAR image preprocessing. RRD simplifies the process of RD, therefore speeds up the computation. The experimental results show that a SAR image can be automated geocoded in 30 s using the single CPU (3 GHz) with 1 G memory and an accuracy of 10 m is attainable with this method.

Raw signal processing of stripmap bistatic synthetic aperture radar

Under the translational invariant (TI) configuration of stripmap imaging bistatic synthetic aperture radar (BISAR), the frequency domain expression of signal model is developed. Two forms, with an approximation of extracting the range dependence and an accurate iterative solution, as well as their respective focusing methods, that is the approximated solution method and the iterative solution method are presented here. The range-Doppler method is extended to the TI configuration of BISAR. Imaging simulation of the point targets and comparison with the bistatic backprojection method shows the feasibility of these methods as well as their merits and demerits.

Web Application System with Synthetic Aperture Rader Image Processing for Education

Remotely sensed images observed by synthetic aperture radar (SAR) become to be more significant for a variety of purposes. It is necessary to process and focus SAR images at a user's side for required precision. This paper presents a concept, a system structure, and an implementation method for a web application system with a SAR image processing for education. The system employs Ajax technology in consideration of current computer and network systems. This system has three software components, a SAR server, an HTTP server, and a web browser in each terminal computer. The SAR server is the main component for managing the SAR database and processing all SAR data sets. The range-Doppler method is adopted as a focusing algorithm. Three displaying measures are newly introduced since the SAR images are sets of mass complex number pixels. Operation of SAR image, sample processed images are shown to exhibit actual examples of processing ALOS PALSAR (Advanced Land Observing Satellite Phased Array type L-band SAR) data. From step-by-step processing results, the proposed web application system was demonstrated to provide a useful graphical user interface (GUI) and to produce the SAR image with adjusted parameters by using dialogs.